Polygenic scores via penalized regression on summary statistics
نویسندگان
چکیده
منابع مشابه
Polygenic scores using summary statistics via penalized regression
Polygenic scores (PGS) summarize the genetic contribution of a person’s genotype to a disease or phenotype. They are useful in a wide variety of analyses of genetic data. Many possible ways of calculating polygenic scores have been proposed, and recently there is much interest in methods that incorporate information available in published summary statistics. As there is no inherent information ...
متن کاملMarginal longitudinal semiparametric regression via penalized splines.
We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achie...
متن کاملThe case-crossover design via penalized regression
BACKGROUND The case-crossover design is an attractive alternative to the classical case-control design which can be used to study the onset of acute events if the risk factors of interest vary in time. By comparing exposures within cases at different time periods, the case-crossover design does not rely on control subjects which can be difficult to acquire. However, using the standard method of...
متن کاملGeneralized Nonparametric Regression via Penalized Likelihood
We consider the asymptotic analysis of penalized likelihood type estimators for generalized non-parametric regression problems in which the target parameter is a vector valued function defined in terms of the conditional distribution of a response given a set of covariates, A variety of examples including ones related to generalized linear models and robust smoothing are covered by the theory. ...
متن کاملNonparametric M-quantile Regression via Penalized Splines
Quantile regression investigates the conditional quantile functions of a response variables in terms of a set of covariates. Mquantile regression extends this idea by a “quantile-like” generalization of regression based on influence functions. In this work we extend it to nonparametric regression, in the sense that the M-quantile regression functions do not have to be assumed to be linear, but ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Genetic Epidemiology
سال: 2017
ISSN: 0741-0395
DOI: 10.1002/gepi.22050